For the things we have to learn before we can do them, we learn by doing them. ~Aristotle

About This Blog

Welcome to a blog by just another Technology Enthusiast.

Since 2007, I am writing this blog to organize my learning on DB/DWH/ETL/BI/Big Data (Hadoop/Spark)/Analytics concepts, architecture, development & performance tuning. Currently, I am posting/documenting my learning in my own way (notes, examples, workshops etc), but I try to mention the source of learning in the references for visitors to explore further.

Again, this blog, not necessarily, covers the topic from scratch neither it promises to be accurate enough to be implemented directly, hence, please test and verify the learning on your dev/test environment before implementing.

What is it?The Internet of Things (IoT) is the ability for things that contain
embedded technologies to sense, communicate, interact, and collaborate
with other things, thus creating a network of physical objects. In
recent years this concept has gained enormous momentum, and is now one
of the most talked about things in the world of technology today. At
this rapid rate of growth, it is projected that there will be
approximately 26 billion connected devices by 2020.

Wireless TechnologiesRFID - identify and track tags attached to objects (using EM fields)NFC - a set of communication protocols to enable two electronic devices communicateWiFi - allows electronic devices to connect to a WLANBLE - wireless technology standard for PANsXBee - a family of form factor compatible radio modulesZigbee - a mesh network specification for low-power WLANs that cover a large area

Why is it required?For Consumer-Ability to remotely monitor and control devices for peace of mind-Improve energy efficiency of household devices-Extends lifecycle for products, through the ability to update-Ability to integrate multiple connected products for improved customer experience-Ability for products to manage themselvesFor Enterprise-Gain insight into customer usage and device performance to improve future products-Open new opportunity to monetize value added service around product usage-Better insight into supply chain management-Ability to update products in the field to enhance capabilities and extend lifecycle

Latest Trends by Gartner–Spending on IoT services will reach of $235 billion in 2016, up 22% from 2015.–In
terms of hardware spending, spending on consumer applications will
total $546 billion, and the use of connected things in the enterprise
will drive $868 billion in 2016.– 6.4 billion connected things will be in use worldwide in 2016, up 30% from 2015, reaching 20.8 billion by 2020.–In 2016, 5.5 million new things will get connected every day.–More
than half of major new business processes and systems will incorporate
some element of the Internet of Things (IoT) by 2020.–Through 2018, 75% of IoT projects will take up to twice as long as planned.–By
2020, a black market exceeding $5 billion will exist to sell fake
sensor and video data for enabling criminal activity and protecting
personal privacy.-By 2020, addressing compromises in IoT security
will have increased security costs to 20% of annual security budgets,
from less than one percent in 2015.

Coursera now offers a Data Science Specialization. The courses are taught by Johns Hopkins University. If you would like to earn a Specialization Certificate, each course will cost you $49 otherwise you can take the courses for free without earning the certificate.The Specialization consists of the following courses. You must complete all courses for the certification. If you are not interested in the certificate, you can take any or all the courses.The Data Scientist’s ToolboxAn introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with.R ProgrammingHow to program in R and how to use R for effective data analysis. Getting and Cleaning DataThe basic ways that data can be obtained from the web, from APIs, from databases and from colleagues in various formats. Exploratory Data AnalysisThe essential exploratory techniques for summarizing dataReproducible ResearchThe concepts and tools behind reporting modern data analyses in a reproducible manner.Statistical InferenceThe process of drawing conclusions about populations or scientific truths from data. Regression ModelsAn outcome to a set of predictors of interest using linear assumptions.Practical Machine LearningThe basic components of building and applying prediction functions with an emphasis on practical applications. Developing Data ProductsData products automate complex analysis tasks or use technology to expand the utility of a data informed model, algorithm or inference.Workshop: Capstone ProjectReferences:Data Science Specialization

Hierarchical Queries Overview
-can select rows in a hierarchical order using the hierarchical query clause
-evaluation process
--JOINs
--CONNECT BY
--WHERE
-hierarchy formation
--selects the root row(s) of the hierarchy (START WITH)
--selects the child rows of each root row and so on
--eliminates child rows based on WHERE clause (individually)

CONNECT BY: specifies the relationship between parent rows and child rows of the hierarchy
PRIOR: to refer to the parent row